def make_large_variation_figure(figsize = (21,23)):
fig = plt.subplots(2,4,figsize=figsize)
plt.subplots_adjust(wspace=0.05, hspace = 0.14)
plt.subplot(2,4,1)
fid_qty = (np.log10(case_fid.mstar))
all_qtys = []
all_qtys.append([np.log10(cases_tau_gmc[i].mstar) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_in[i].mstar) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_eq[i].mstar) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma_gmc[i].mstar) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma[i].mstar) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys, llim = 10, ulim = 13.5,save_fname='varparam_mass', nofig=True)
plt.subplot(2,4,2)
fid_qty = (np.log10(case_fid.ha_lums))
all_qtys = []
all_qtys.append([np.log10(cases_tau_gmc[i].ha_lums) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_in[i].ha_lums) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_eq[i].ha_lums) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma_gmc[i].ha_lums) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma[i].ha_lums) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys,
llim = -5., ulim = -1.5, xlabel=r'log H$\alpha$ [L$_\odot$/M$_\odot$]',
save_fname='varparam_ha',plot_yticks=False, nofig=True)
plt.subplot(2,4,3)
fid_qty = (np.log10(case_fid.nuv_vals))
all_qtys = []
all_qtys.append([np.log10(cases_tau_gmc[i].nuv_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_in[i].nuv_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_eq[i].nuv_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma_gmc[i].nuv_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma[i].nuv_vals) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys,
llim = -18, ulim = -14.7, xlabel=r'log F$_{\nu, {\rm NUV}}$ [L$_\odot/M_\odot$]',
save_fname='varparam_nuv',plot_yticks=False, nofig=True)
plt.subplot(2,4,4)
fid_qty = ((case_fid.hdelta_ews))
all_qtys = []
all_qtys.append([(cases_tau_gmc[i].hdelta_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_in[i].hdelta_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_eq[i].hdelta_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma_gmc[i].hdelta_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma[i].hdelta_ews) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys,
llim = -4., ulim = 5.0, xlabel=r'H$\delta_{\rm EW}$ [$\AA$]',
save_fname='varparam_hdelta',plot_yticks=False, nofig=True)
plt.subplot(2,4,5)
fid_qty = ((case_fid.caH_ews))
all_qtys = []
all_qtys.append([(cases_tau_gmc[i].caH_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_in[i].caH_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_eq[i].caH_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma_gmc[i].caH_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma[i].caH_ews) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys,
llim = 2., ulim = 9.0, xlabel=r'Ca-H$_{\rm EW}$ [$\AA$]',
save_fname='varparam_cah',plot_yticks=True, nofig = True)
plt.subplot(2,4,6)
fid_qty = ((case_fid.caK_ews))
all_qtys = []
all_qtys.append([(cases_tau_gmc[i].caK_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_in[i].caK_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_eq[i].caK_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma_gmc[i].caK_ews) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma[i].caK_ews) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys,
llim = 0., ulim = 7.0, xlabel=r'Ca-K$_{\rm EW}$ [$\AA$]',
save_fname='varparam_cak',plot_yticks=False, nofig = True)
plt.subplot(2,4,7)
fid_qty = (np.log10(case_fid.u_vals))
all_qtys = []
all_qtys.append([np.log10(cases_tau_gmc[i].u_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_in[i].u_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_tau_eq[i].u_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma_gmc[i].u_vals) for i in range(len(cases_sigma))])
all_qtys.append([np.log10(cases_sigma[i].u_vals) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys,
llim = -16.5, ulim = -14.7, xlabel=r'log F$_{\nu, {\rm u}}$ [L$_\odot/$M$_\odot$]',
save_fname='varparam_u',plot_yticks=False, nofig = True)
plt.subplot(2,4,8)
fid_qty = ((case_fid.dn4000_vals))
all_qtys = []
all_qtys.append([(cases_tau_gmc[i].dn4000_vals) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_in[i].dn4000_vals) for i in range(len(cases_sigma))])
all_qtys.append([(cases_tau_eq[i].dn4000_vals) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma_gmc[i].dn4000_vals) for i in range(len(cases_sigma))])
all_qtys.append([(cases_sigma[i].dn4000_vals) for i in range(len(cases_sigma))])
param_qtys = [psd_var_tau_gmc, psd_var_tau_in, psd_var_tau_eq, psd_var_sigma_gmc, psd_var_sigma]
make_var_param_figures(fid_qty, all_qtys, param_qtys, llim = 0.9, ulim = 2.0, xlabel=r'D$_n$(4000) ${\rm \AA}$',
save_fname='varparam_dn4000',plot_yticks=False, nofig = True)
plt.savefig('figures/varparam_all.png',bbox_inches='tight')
make_large_variation_figure()
